Simple MPPI Implementation with Python
Model Predictive Path-Integral (MPPI) Control [G. Williams et al., 2018] is a promising sampling-based optimal control algorithm.
This repository is for understanding the basic idea of the algorithm.
Dependency
-
uv
- A simple and fast Python package manager.
Refer to the official documentation for one-command installation.
- Only
numpy, matplotlib, notebook are needed to run all scripts in this repository.
-
ffmpeg
-
mp4 movie writer
-
installation details
- For Ubuntu Users
sudo apt-get updatesudo apt-get -y install ffmpeg
- For Windows Users
- Install scoop
scoop install ffmpeg
- For macOS Users
- Check the official website if necessary
Setup
[Option 1] Native environment
git clone https://github.com/MizuhoAOKI/python_simple_mppi.git
cd python_simple_mppi
uv sync
[Option 2] Docker environment
CLICK HERE TO EXPAND
-
Install docker.
-
Clone the project repository.
cd <path to your workspace>
git clone https://github.com/MizuhoAOKI/python_simple_mppi.git
-
Run setup to build the docker image, launch the docker container and get into the bash inside. Building the image might take a few minutes.
cd <path to your workspace>/python_simple_mppi
docker compose run --rm dev
This command will automatically build the Docker image if needed.
Once the container starts, any changes made in the local repository on the host will be reflected inside the container, and vice versa.
Usage
Path Tracking
Simple Path Tracking
-
Run simulation
cd python_simple_mppi
uv run scripts/mppi_pathtracking.py
-
Run jupyter notebook if you would like to check mathematical explanations on the algorithm.
cd python_simple_mppi
uv run jupyter notebook --notebook-dir=. notebooks/mppi_pathtracking.ipynb
Path Tracking with Obstacle Avoidance
-
Run simulation
cd python_simple_mppi
uv run scripts/mppi_pathtracking_obav.py
-
Run jupyter notebook if you would like to check mathematical explanations on the algorithm.
cd python_simple_mppi
uv run jupyter notebook --notebook-dir=. notebooks/mppi_pathtracking_obav.ipynb
Pendulum
-
Run simulation to swing up a pendulum.
cd python_simple_mppi
uv run scripts/mppi_pendulum.py
-
Run jupyter notebook if you would like to check mathematical explanations on the algorithm.
cd python_simple_mppi
uv run jupyter notebook --notebook-dir=. notebooks/mppi_pendulum.ipynb
CartPole
-
Run simulation of cartpole
cd python_simple_mppi
uv run scripts/mppi_cartpole.py
-
Run jupyter notebook if you would like to check mathematical explanations on the algorithm.
cd python_simple_mppi
uv run jupyter notebook --notebook-dir=. notebooks/mppi_cartpole.ipynb
References
- G. Williams et al. “Information-Theoretic Model Predictive Control: Theory and Applications to Autonomous Driving”
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